Testing veloViz with distance threshold

Setup and get data from scVelo

Get whole trajectory

load complete adata from previous run

Get missing intermediates

load missing intermediate adata from previous run

Run velocyto - whole trajectory

Extract count data..

Filter genes

(Downsample cells to make things easier)

Normalize for dimensional reduction

## Warning in if (!class(counts) %in% c("dgCMatrix", "dgTMatrix")) {: the condition
## has length > 1 and only the first element will be used

## Converting to sparse matrix ...

Dimensional reduction

Run velocyto on panc data

## Warning in if (!class(counts) %in% c("dgCMatrix", "dgTMatrix")) {: the condition
## has length > 1 and only the first element will be used

## Converting to sparse matrix ...

Scores of observed and projected states in PC space

veloViz - whole trajectory

Graph visualization on subset of cells from PC coordinates

Run velocyto - missing intermediates

Extract count data..

Filter genes

(Downsample cells to make things easier)

Normalize for dimensional reduction

## Warning in if (!class(counts) %in% c("dgCMatrix", "dgTMatrix")) {: the condition
## has length > 1 and only the first element will be used

## Converting to sparse matrix ...

Dimensional reduction

Run velocyto on panc data

## Warning in if (!class(counts) %in% c("dgCMatrix", "dgTMatrix")) {: the condition
## has length > 1 and only the first element will be used

## Converting to sparse matrix ...

Scores of observed and projected states in PC space

veloViz - missing intermediates

Graph visualization from PC coordinates

Changing veloviz parameters

Above, I used k=30 for direct comparison to cellRank graph which computes distances to K=30 nearest neighbors uses. However, this might not be where veloviz performs best.

Comparing graphs

Compare mean distance between cells before and after the gap normalized by max distance between any two cells for each graph.